Astronomy and Astrophysics – Astrophysics – Instrumentation and Methods for Astrophysics
Scientific paper
2012-01-23
Astronomy and Astrophysics
Astrophysics
Instrumentation and Methods for Astrophysics
10 pages, 3 figures. To appear in the ADASS XXI (Paris, 2011) conference proceedings
Scientific paper
I describe the performance of the CRBLASTER computational framework on a 350-MHz 49-core Maestro Development Board (MDB). The 49-core Interim Test Chip (ITC) was developed by the U.S. Government and is based on the intellectual property of the 64-core TILE64 processor of the Tilera Corporation. The Maestro processor is intended for use in the high radiation environments found in space; the ITC was fabricated using IBM 90-nm CMOS 9SF technology and Radiation-Hardening-by-Design (RHDB) rules. CRBLASTER is a parallel-processing cosmic-ray rejection application based on a simple computational framework that uses the high-performance computing industry standard Message Passing Interface (MPI) library. CRBLASTER was designed to be used by research scientists to easily port image-analysis programs based on embarrassingly-parallel algorithms to a parallel-processing environment such as a multi-node Beowulf cluster or multi-core processors using MPI. I describe my experience of porting CRBLASTER to the 64-core TILE64 processor, the Maestro simulator, and finally the 49-core Maestro processor itself. Performance comparisons using the ITC are presented between emulating all floating-point operations in software and doing all floating point operations with hardware assist from an IEEE-754 compliant Aurora FPU (floating point unit) that is attached to each of the 49 cores. Benchmarking of the CRBLASTER computational framework using the memory-intensive L.A.COSMIC cosmic ray rejection algorithm and a computational-intensive Poisson noise generator reveal subtleties of the Maestro hardware design. Lastly, I describe the importance of using real scientific applications during the testing phase of next-generation computer hardware; complex real-world scientific applications can stress hardware in novel ways that may not necessarily be revealed while executing simple applications or unit tests.
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